Computer-aided image analysis of biological material has become popular during the last years. For instance, computer-aided processes for counting and classifying white blood cells in a blood smear have been developed. These types of tests are e.g. an important step in the process of determining whether a patient suffers from an infection, allergy or blood cancer.
In order to be able to make a reliable analysis it is of great importance that the image data is of proper quality, involving for instance that the image data is sharp, i.e. captured with accurate focus settings.
Today, a common method for finding an in-focus position involves a first step of capturing several images at different positions, a second step of identifying high frequency components in the captured images and a third step of determining the image with the highest amount of high frequency components. The position corresponding to the image with the highest amount of high frequency components is thereafter chosen to be the in-focus position. In order to find the in-focus position it is not unlikely that as much as 20 images at different positions have to be captured.
Moreover, if image data is to be captured for each of the objects to be classified, the image capturing process must be repeated a number of times, e.g. 20 times, for every object, which in turn implies that a large amount of image data has to be captured for every sample and that the vision inspection system must be readjusted a large number of times for every sample. Hence, this method consumes a lot of time and the large amount of readjustments may wear out the system.